1. Field of the Invention
The present invention relates to methods for selecting internet content for presentation to a user, and more particularly, methods, systems, and computer programs for presenting news articles related to a news article selected by a user.
2. Description of the Related Art
The recent decade has witnessed an explosive growth of online news. According to a recent report, more than 123 million people visited news websites such as Yahoo!™ News in May 2010, representing 57 percent of the total U.S. internet audience, with each visitor reading 43 pages on average. These numbers have been steadily increasing over the past years and show the growing appeal of reading news online.
Recommending interesting news articles to users has become extremely important for internet providers looking to maintain users' interest. While existing Web services, such as Yahoo! and Digg™, attract users' initial clicks, methods to engage users after their initial visit is largely under explored.
One important advantage of online news over traditional newspapers is that the former can be augmented with hyperlinks to other related news. When a user is reading a news article, the user may also be interested in related articles that logically flow from the content of the current page. This process is referred to herein as post-click news recommendation, which has the goal of promoting users' navigation to other web pages. However, if the recommended articles are not logically related to the article being read, the recommended articles will fail to capture user interest, and users' overall satisfaction will decrease. Therefore, an effective post-click news recommendation is critical to online news websites.
In some solutions today, post-click news recommendation is typically done by editors that search through a corpus of news documents. The process is expensive and cumbersome, and is also limited by the editors' familiarity with the news topics.
It is in this context that embodiments arise.